Predicting Transcriptional and Epigenetic Networks in Cancer from Sequencing Data

从测序数据预测癌症中的转录和表观遗传网络

• 批准号: 8838736
• 负责人: Jun S Song
• 金额: $ 32.9万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-12-16 至 2016-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8838736
• 关键词: Address; Apoptosis; Binding; Bioinformatics; Boxing; Cell Cycle; ChIP-seq; Chromatin Structure; Code; Computer software; Computing Methodologies; DNA; DNA Sequence Analysis; Data; Data Quality; Data Set; E-Box Elements; Ensure; Enzymes; Epigenetic Process; Failure; Gene Expression; Gene Targeting; General Transcription Factors; Generations; Genetic; Genome; High-Throughput DNA Sequencing; Human; Human Genome; Incidence; Informatics; Large-Scale Sequencing; Malignant Neoplasms; Maps; Methods; MicroRNAs; Modification; Normal Cell; Oncogenes; Oncogenic; Other Genetics; Process; Protein Binding; Proteins; Quality Control; Recruitment Activity; Regulator Genes; Research; Resistance; Resources; Retrotransposon; Signal Transduction; Skin Cancer; Software Validation; Source; Specificity; Statistical Methods; Technology; Testing; Therapeutic; Transcriptional Regulation; Tumor Suppressor Proteins; United States National Institutes of Health; Untranslated RNA; Visualization software; Work; anticancer research; base; cancer cell; cancer genomics; cancer type; chemotherapy; computerized tools; epigenomics; experience; genome-wide; histone modification; melanocyte; melanoma; microphthalmia-associated transcription factor; next generation sequencing; novel; platform-independent; success; tool; transcription factor; transcriptome sequencing; tumor progression

DESCRIPTION (provided by applicant): This project aims to develop bioinformatic resources for processing and integrating the large-scale sequencing data that are rapidly emerging for studying oncogenic transcription factors (TFs) in cancer research. While our methods will be applicable to general TFs, we will develop our tools by focusing on microphthalmia-associated transcription factor (MITF), a key onco-protein frequently amplified in melanoma. MITF is perhaps the most intensely studied TF in melanoma, being responsible for turning multiple signals into a transcriptional control of proliferation, survival, and invasion. Studying the mechanisms of an oncogenic TF, such as MITF, and comprehensively identifying its direct target genes thus remain important unsolved problems in cancer research. Cancer genomics based on high-throughput DNA sequencing is now rapidly generating enormous amounts of genetic and epigenetic data that can collectively reveal how MITF functions as a potent regulator of melanoma progression. Analyzing such massive heterogeneous datasets is frequently challenged by both sequencing failures and the lack of analysis methods for integrating and interpreting the resulting information. The proposed tools will address these urgent problems: (1) We will develop a stand-alone platform- independent quality control visualization software for ChIP-seq and RNA-seq data. Our software package will automatically test and graphically summarize the quality of data and also suggest potential sources of failure; (2) We will develop and apply computational tools for discovering cooperating TFs of MITF. TF binding activity in itself is often insufficient to regulate gene expression, suggesting that specific combinations of cooperating factors crucially determine MITF's ability to transcribe key oncogenes in melanoma. We will thus computationally identify and experimentally validate cooperating factors of MITF by combining ChIP-seq data with DNA sequence analysis; (3) We will develop and apply statistical methods for inferring the epigenetic changes that are both controlled by and guiding MITF and, as a result, identify aberrant epigenetic modifications that disrupt normal MITF functions; (4) As aberrant expression of non-coding RNAs (ncRNAs) and retrotransposons can critically alter cell cycle, apoptosis and proliferation, we will identify active ncRNAs and retrotransposons in melanoma and discover their transcriptional regulators. These results will help reveal the transcriptional and epigenetic network of MITF in melanoma and produce valuable resources applicable to other cancers.

描述(申请人提供)：该项目旨在开发生物信息学资源，用于处理和整合快速出现的大规模测序数据，以研究癌症研究中的致癌转录因子(TF)。虽然我们的方法将适用于一般的TF，但我们将通过专注于小眼球相关转录因子(MITF)来开发我们的工具，MITF是一种在黑色素瘤中经常放大的关键癌蛋白。MITF可能是黑色素瘤中研究最深入的转铁蛋白，负责将多种信号转变为对增殖、存活和侵袭的转录控制。因此，研究致癌因子(如MITF)的作用机制并全面鉴定其直接靶基因仍然是癌症研究中尚未解决的重要问题。基于高通量DNA测序的癌症基因组学现在正在迅速产生大量的遗传和表观遗传学数据，这些数据可以共同揭示MITF如何作为黑色素瘤进展的有效调节因子发挥作用。分析如此庞大的异质数据集经常受到测序失败和缺乏整合和解释结果信息的分析方法的挑战。这些工具将解决这些亟待解决的问题：(1)我们将开发一个独立于平台的、针对CHIP-SEQ和RNA-SEQ数据的质量控制可视化软件。我们的软件包将自动测试并以图形方式汇总数据质量，并提出潜在的故障来源；(2)我们将开发和应用计算工具，以发现MITF的合作函数。Tf结合活性本身往往不足以调节基因表达，这表明协同因素的特定组合至关重要地决定了MITF转录黑色素瘤关键癌基因的能力。因此，我们将通过将CHIP-SEQ数据与DNA序列分析相结合，通过计算确定和实验验证MITF的协同因子；(3)我们将开发和应用统计学方法来推测由MITF控制和指导MITF的表观遗传变化，从而发现扰乱正常MITF功能的异常表观遗传修饰；(4)由于非编码RNA(NcRNAs)和反转座子的异常表达可以关键地改变细胞周期、细胞凋亡和增殖，我们将研究黑色素瘤中活跃的ncRNAs和逆转座子，并发现它们的转录调控因子。这些结果将有助于揭示MITF在黑色素瘤中的转录和表观遗传网络，并产生适用于其他癌症的宝贵资源。